class_docstr: An `EventMultiplexer` manages access to multiple `EventAccumulator`s.
  
  Each `EventAccumulator` is associated with a `run`, which is a self-contained
  TensorFlow execution. The `EventMultiplexer` provides methods for extracting
  information about events from multiple `run`s.
  
  Example usage for loading specific runs from files:
  
  ```python
  x = EventMultiplexer({'run1': 'path/to/run1', 'run2': 'path/to/run2'})
  x.Reload()
  ```
  
  Example usage for loading a directory where each subdirectory is a run
  
  ```python
  (eg:) /parent/directory/path/
        /parent/directory/path/run1/
        /parent/directory/path/run1/events.out.tfevents.1001
        /parent/directory/path/run1/events.out.tfevents.1002
  
        /parent/directory/path/run2/
        /parent/directory/path/run2/events.out.tfevents.9232
  
        /parent/directory/path/run3/
        /parent/directory/path/run3/events.out.tfevents.9232
  x = EventMultiplexer().AddRunsFromDirectory('/parent/directory/path')
  (which is equivalent to:)
  x = EventMultiplexer({'run1': '/parent/directory/path/run1', 'run2':...}
  ```
  
  If you would like to watch `/parent/directory/path`, wait for it to be created
    (if necessary) and then periodically pick up new runs, use
    `AutoloadingMultiplexer`
  @@Tensors
docstr: Get index of runs and assets for a given plugin.
  
  Args:
    plugin_name: Name of the plugin we are checking for.
  
  Returns:
    A dictionary that maps from run_name to a list of plugin
      assets for that run.
docstr_tok: ["Get","index","of","runs","and","assets","for","a","given","plugin",".","Args",":","plugin_name",":","Name","of","the","plugin","we","are","checking","for",".","Returns",":","A","dictionary","that","maps","from","run_name","to","a","list","of","plugin","assets","for","that","run","."]
code: def PluginAssets(self, plugin_name):
      """Get index of runs and assets for a given plugin.
  
      Args:
        plugin_name: Name of the plugin we are checking for.
  
      Returns:
        A dictionary that maps from run_name to a list of plugin
          assets for that run.
      """
      with self._accumulators_mutex:
          # To avoid nested locks, we construct a copy of the run-accumulator map
          items = list(self._accumulators.items())
  
      return {
          run: accum.PluginAssets(plugin_name) for run, accum in items
      }
  
imports: import os
  import queue
  import threading
  from typing import Optional
  from tensorboard.backend.event_processing import directory_watcher
  from tensorboard.backend.event_processing import plugin_event_accumulator
  from tensorboard.backend.event_processing import io_wrapper
  from tensorboard.util import tb_logging
label_desc: Use image node_id 5 for calling the EventMultiplexer obj's underlying member method code with example usage: obj.PluginAssets(plugin_name) and returns: unknown